Determining values of a variable at a particular percentile in a normal distribution
From playlist Unit 2: Normal Distributions
Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.
From playlist Learning medical statistics with python and Jupyter notebooks
An introduction to Regression Analysis
Regression Analysis, R squared, statistics class, GCSE Like us on: http://www.facebook.com/PartyMoreStudyLess Related Videos Playlist on Linear Regression http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C Using SPSS for Multiple Linear Regression http://www.youtube.com/playlist?li
From playlist Linear Regression.
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
How to calculate Linear Regression using R. http://www.MyBookSucks.Com/R/Linear_Regression.R http://www.MyBookSucks.Com/R Playlist http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C
From playlist Linear Regression.
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Ex: Comparing Linear and Exponential Regression
This video provides an example on how to perform linear regression and exponential regression on the TI84. The best model is identified based up the value of R^2. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com
From playlist Solving Applications Using Exponential Equations / Compounded and Continuous Interest / Exponential Regression
Regularization Part 1: Ridge (L2) Regression
Ridge Regression is a neat little way to ensure you don't overfit your training data - essentially, you are desensitizing your model to the training data. It can also help you solve unsolvable equations, and if that isn't bad to the bone, I don't know what is. This StatQuest follows up on
From playlist StatQuest
Kaggle Reading Group: Neural Networks and Neural Language Models | Kaggle
Join Kaggle Data Scientist Rachael as she reads through an NLP paper! Today's paper is the chapter "Neural Networks and Neural Language Models" from "Speech and Language Processing" by Daniel Jurafsky & James H. Martin. This chapter is new to the currently-in-progress edition of the book,
From playlist Kaggle Reading Group | Kaggle
understanding of logistic regression and its cost function. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6
From playlist Machine Learning
Data Science - Part IV - Regression Analysis and ANOVA Concepts
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of linear regression analysis, interaction terms, ANOVA, optimization, log-leve
From playlist Data Science
STAT501, 5-3 Multiple linear regression example
From playlist STAT 501
Review of Block C, weeks 9 - 12, for QBA 337.
From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)
Data Analysis 9: Data Regression - Computerphile
Real life doesn't fit into neat categories - Dr Mike Pound on some different ways to regress your data. This is part 9 of the Data Analysis Learning Playlist: https://www.youtube.com/playlist?list=PLzH6n4zXuckpfMu_4Ff8E7Z1behQks5ba This Learning Playlist was designed by Dr Mercedes Torr
From playlist Data Analysis with Dr Mike Pound
Deep Learning Applications by Rina Panigrahy
Statistical Physics Methods in Machine Learning DATE: 26 December 2017 to 30 December 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "t
From playlist Statistical Physics Methods in Machine Learning
Lecture 05 Neural Networks Learning
Machine Learning by Andrew Ng [Coursera] 0501 Cost function 0502 Backpropagation algorithm 0503 Backpropagation intuition 0504 Implementation note: Unrolling parameters 0505 Gradient checking 0506 Random initialization 0507 Putting it together 0508 Autonomous driving example
From playlist Machine Learning by Professor Andrew Ng
(ML 10.2) Posterior for linear regression (part 1)
How to compute the posterior distribution for the weight vector w under a Bayesian model for linear regression.
From playlist Machine Learning